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About course

FSF3847 Convex Optimization with Engineering Applications 6.0 credits

Administer About course

This course is a graduate course, given jointly by the School of Electrical Engineering, and the Department of Mathematics at KTH. The course is primarily not intended for students with focus on optimization, but rather aimed for students from other areas.

Course offering missing for current semester as well as for previous and coming semesters
Headings with content from the Course syllabus FSF3847 (Spring 2019–) are denoted with an asterisk ( )

Content and learning outcomes

Course contents

  • Convex sets

  • Convex functions

  • Convex optimization

  • Linear and quadratic programming

  • Geometric and semidefinite programming

  • Duality

  • Smooth unconstrained minimization

  • Sequential unconstrained minimization

  • Interior-point methods

  • Decomposition and large-scale optimization

  • Applications in estimation, data fitting, control and communications

Intended learning outcomes

After completed course, the student should be able to

  • characterize fundamental aspects of convex optimization (convex functions, convex sets, convex optimization and duality);

  • characterize and formulate linear, quadratic, geometric and semidefinite programming problems;

  • implement, in a high level language such as Matlab, crude versions of modern methods for solving convex optimization problems, e.g., interior methods;

  • solve large-scale structured problems by decomposition techniques;

  • give examples of applications of convex optimization within statistics, communications, signal processing and control.

Course disposition

No information inserted

Literature and preparations

Specific prerequisites

The course requires basic knowledge of calculus and linear algebra.

Recommended prerequisites

No information inserted

Equipment

No information inserted

Literature

S. Boyd och L. Vandenberghe, Convex Optimization, Cambridge University Press, 2004, ISBN: 0521833787

Examination and completion

If the course is discontinued, students may request to be examined during the following two academic years.

Grading scale

P, F

Examination

  • INL1 - Assignment, 6.0 credits, grading scale: P, F

Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.

The examiner may apply another examination format when re-examining individual students.

Other requirements for final grade

Successful completion of homework assignments and the presentation of a short lecture on a special topic.

There will be a total of four sets of homework assignments distributed during the course. Late homework solutions are not accepted.

The short lecture should sum up the key ideas, techniques and results of a (course-related) research paper in a clear and understandable way to the other attendees.

Opportunity to complete the requirements via supplementary examination

No information inserted

Opportunity to raise an approved grade via renewed examination

No information inserted

Examiner

Profile picture Anders Forsgren

Ethical approach

  • All members of a group are responsible for the group's work.
  • In any assessment, every student shall honestly disclose any help received and sources used.
  • In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.

Further information

Course web

Further information about the course can be found on the Course web at the link below. Information on the Course web will later be moved to this site.

Course web FSF3847

Offered by

SCI/Mathematics

Main field of study

This course does not belong to any Main field of study.

Education cycle

Third cycle

Add-on studies

No information inserted

Contact

Anders Forsgren (andersf@kth.se)

Postgraduate course

Postgraduate courses at SCI/Mathematics